AI Transformation Manager

Convert business priorities into high-value AI products and agentic workflows, owning discovery, process redesign, product direction, agile backlog and benefits realization.

·        Lead value-discovery and process-design workshops with business and technology stakeholders.

·        Map current workflows, decisions, hand-offs, pain points, controls and performance baselines.

·        Prioritize agentic use cases based on value, feasibility, risk and time to impact.

·        Act as product owner or product-management lead for client delivery, maintaining outcomes, roadmap and backlog.

·        Define business cases, KPIs, benefit owners and measurement approaches.

·        Coordinate user adoption, operating-model changes and transition to business ownership.

·        7+ years in management consulting, digital transformation, product management or process improvement.

·        Strong experience in business cases, process redesign, agile delivery and executive facilitation.

·        Ability to translate business needs into clear product outcomes and acceptance criteria.

·        Working understanding of AI, agents, data dependencies, human oversight and automation.

·        Working knowledge of agentic solution concepts, including tool calling, workflow orchestration, memory, retrieval-augmented generation, human-in-the-loop controls, evaluation and observability.

·        Ability to convert a business process into agent roles, tools, decision points, structured inputs and outputs, exception paths, acceptance criteria and measurable value hypotheses.

·        Familiarity with platforms and frameworks used by delivery teams, such as LangChain and LangGraph, Microsoft Agent Framework or Semantic Kernel, OpenAI Agents SDK, Microsoft Copilot Studio and workflow automation platforms.

·        Experience using Agile product-management tooling such as Azure DevOps or Jira to manage epics, user stories, acceptance criteria, dependencies, releases and benefits measures.

·        Value of prioritized use cases

·        Backlog quality and stakeholder alignment

·        Speed from discovery to usable release

·        Benefits measured after deployment

·        Client adoption and satisfaction

·        Other members of the AI Transformation & Agentic Systems Practice

·        PwC sector, functional, cloud, cyber, risk, Responsible AI and change specialists

·        Client business owners, product owners, technology teams and operational users

·        Technology alliance and implementation partners where relevant

·        Support proposals, client workshops and market development appropriate to seniority.

·        Contribute reusable methods, patterns, code, assets and lessons learned.

·        Coach colleagues and participate in the capability’s continuous learning agenda.

·        Uphold PwC quality, independence, confidentiality and risk-management requirements.

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